Vice President, Data Science & Product Analytics

What you'll do

• Lead product analytics and performance diagnostics across the marketplace
• Conduct deep-dive investigations into auction outcomes, click & conversion funnels, supply quality, advertiser ROI, financial analysis, user behavior, and ranking logic
• Develop frameworks to surface hidden performance issues, inefficiencies, and optimization opportunities
• Identify problems, surface opportunities, and influence product direction partnering with Product, Engineering, Design, FP&A and Commercial leadership
• Measure product health, discover opportunities, and forecast outcomes
• Provide executive-facing insights that shape roadmap priorities and investment decisions
• Diagnose performance issues across auctions, ranking and relevance, and conversion funnels
• Analyze supply–demand dynamics and marketplace balance
• Evaluate performance by advertiser, query, geo, device, and vertical segments
• Translate complex data into clear, prioritized problem statements for product teams
• Actively surface previously unknown risks and opportunities
• Identify leading indicators of performance degradation or growth potential
• Influence product strategy by connecting analytical findings directly to business impact, trade-offs, and expected outcomes
• Guide product teams toward highest-leverage opportunities using data-backed narratives
• Own experimentation, causal inference, and incrementality frameworks to ensure decisions are grounded in validated impact
• Partner with Product, Engineering, and Data Engineering to design, run, and interpret experiments evaluating features, ranking changes, and marketplace policies
• Standardize measurement, metrics, and reporting across product teams
• Build scalable analytics and experimentation systems delivering fast, trusted insights from complex event-level data
• Prepare and deliver clear, compelling narratives connecting product behavior to business outcomes for executives

Requirements

• Deep expertise in product analytics and experimentation including A/B and multivariate testing, incrementality and lift analysis, funnel and cohort analysis, and KPI forecasting
• Strong statistical foundation with ability to interpret complex experimental and causal results
• Advanced SQL skills and experience working with large, event-level datasets
• Fluency with modern analytics, data platforms, and visualization tools such as Tableau and Databricks
• Strong product and business intuition with a track record of influencing product strategy and connecting insights to growth, efficiency, and P&L impact
• Experience operating at the intersection of product, analytics, and business
• Demonstrated ability to lead senior analytical teams and communicate complex insights to executive audiences
• Degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, or similar)
• 12+ years of experience in product analytics, data science, experimentation, or performance measurement
• Background in search, performance marketing, adtech, or large-scale marketplaces

Tech stack

Benefits